DBMS > Altibase vs. Apache IoTDB vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. OpenTSDB

System Properties Comparison Altibase vs. Apache IoTDB vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

An enterprise grade, high-performance RDBMS

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Serverless Time Series DBMS

Globally distributed, horizontally scalable, multi-model database service

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

altibase.com

iotdb.apache.org

hyprcubd.com (offline)

azure.microsoft.com/services/cosmos-db

opentsdb.net

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

learn.microsoft.com/azure/cosmos-db

opentsdb.net/docs/build/html/index.html

Developer

Altibase

Apache Software Foundation

Hyprcubd, Inc.

Microsoft

currently maintained by Yahoo and other contributors

Initial release

1999

2018

2014

2011

Current release

v7.3, 2023, August 2023

1.1.0, April 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

AIX
HP-UX
Linux

All OS with a Java VM (>= 1.8)

hosted

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

JSON types

numeric data for metrics, strings for tags

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Native API

gRPC (https)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API
Telnet API

Supported programming languages

C
C++
Java

C
C#
C++
Go
Java
Python
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

token access

Access rights can be defined down to the item level

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